Chromosomal assessment to differentiate histiocytic malignancy from lymphoma in dogs

ABSTRACT

This invention relates generally to the discovery of an improved method to differentiate histiocytic malignancy from lymphoma or hemangiosarcoma in dogs.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a § 371 U.S. National Stage of InternationalApplication PCT/US2015/025916, filed Apr. 15, 2015, which claims thebenefit of 61/979,775 filed Apr. 15, 2014, Matthew Breen, entitled“CHROMOSOMAL ASSESSMENT TO DIFFERENTIATE HISTIOCYTIC MALIGNANCY FROMLYMPHOMA IN DOGS”, which are hereby incorporated by reference in theirentireties.

1. FIELD OF THE INVENTION

This invention relates generally to the discovery of an improved methodto differentiate histiocytic malignancy from lymphoma andhemangiosarcoma in dogs.

2. BACKGROUND OF THE INVENTION 2.1. Introduction

It is estimated that there are over 300,000 dogs each year in the UnitedStates diagnosed with lymphoma (LSA). Diagnosis of canine lymphomagenerally is made following a variety of clinical and pathologicalassessments, including cytology and/or histopathologic analysis of atumor biopsy specimen. Untreated cases of canine lymphoma rarely survivebeyond three months after diagnosis, but a large proportion (up to 90%)of canine lymphomas are responsive to standard of care (SOC)chemotherapy, using either single agent or multiagent protocols,increasing both the length and quality of an affected dog's life. Mediansurvival with SOC treatment is generally considered to be nine months.

Histiocytic malignancies (HM), frequently reported by pathologists ashistiocytic sarcoma, disseminated histiocytic sarcoma, or malignanthistiocytosis, are less common in the general dog population, estimatedto be diagnosed in fewer than 5,000 cases per year in the US. Theincidence of histiocytic neoplasms, however, is remarkably high in somepurebred dogs, including the Bernese mountain dog, the flat-coatedretriever and the rottweiler. Malignant tumors of histiocytic origingenerally have a very poor prognosis (typical survival is just a fewweeks post diagnosis) and are considered generally unresponsive tocurrent therapeutic options. For example, in the Bernese mountain dog,66% of deaths are reported to be due to cancer (BMDCA Health Survey,2005), of which 47% are attributed to HM, with a further 29% due tolymphoma. These data indicate that ˜75% of all cancers and ˜50% of alldeaths in this breed are due to just these two cancers.

Hemangiosarcomas (HEM) are cancers are tumors of the vascularendothelium, cells that line blood vessels. These cancers representapprox. 2% of all canine cancers and about 5% of all non-cutaneoustumors. Hemangiosarcoma is more common in dogs than any other speciesand develop primarily in the spleen, heart, or liver. Although usuallyan indolent disease, hemangiosarcoma is almost always malignant and canspread rapidly. For the affected dog this generally means that theclinical signs may not present until after the tumors have metastasizedand/or ruptured. Rupture of a hemangiosarcoma may cause the dog toexperience acute shock and collapse. There are clear dog breedpredispositions to hemangiosarcoma. Since hemangiosarcoma can affect thesame tissues as histiocytic malignancies, pathology is required toprovide a confirmed diagnosis.

Fine needle aspiration of a mass may be used to provide cells forcytologic diagnosis, though this has received mixed reviews amongpathologists as the cells of a histiocytic malignancy can look verysimilar to other types of tumors, leading to an inconclusive diagnosis.As such additional tests may need to be performed to obtain a definitivediagnosis. Correct diagnosis of a histiocytic neoplasm currentlyrequires specialized immunohistochemistry (IHC) to distinguish fromother neoplasms with similar histological appearances. However, thisform of analysis is not always readily available, is time consuming,costly, and requires a particular skill set. In addition, the strongassociation between key breeds and the incidence of histiocyticmalignancy has meant that it is not uncommon for histiocytic malignancyto be provided as the most likely differential, solely due to the breedof the patient, even in the absence of appropriate IHC to provide arobust diagnosis.

The ability to accurately distinguish between canine LSA, HEM, and HM isthus an important goal for the veterinary profession, to ensure mostappropriate clinical management of cancer patients. Such an assay wouldoffer considerable value to patient management, adding new approaches torefine diagnosis, and even prognosis.

3. SUMMARY OF THE INVENTION

Described herein, are the foundations for a diagnostic molecular test toseparate canine lymphoma and hemangiosarcoma from a histiocyticmalignancy. The assay is based on significant differences in the DNAcopy number status of selected regions of the canine genome, whenevaluating cells obtained from lymphoma, hemangiosarcoma, andhistiocytic malignancy tumor samples. There is immediate significance tothe veterinary market in being able to readily distinguish these threetypes of cancer, especially for those breeds that are at high risk ofdeveloping these cancers.

Differentiating between histiocytic malignancy and lymphoma: A largecohort of tumor samples pathologically verified as either caninelymphoma or histiocytic malignancy was assembled. Each case was assessedfor copy number status (deletion/loss, balanced, gain) of ˜180,000oligonucleotide probes spaced at 13 kb intervals across the caninegenome. Suitable aberration calling algorithms were used to definecontiguous segments subject to copy number aberration in both cancertypes. Statistical comparison of the two datasets revealed regions ofthe canine genome where the DNA copy number status differedsignificantly between the two cancer groups. Three of the mostsignificant differences were selected for subsequent assessment, basedon segment size. The most significant region, even by itself, offersvery high specificity and sensitivity to distinguish between caninelymphoma and a histiocytic malignancy. A multivariate/combineddiagnostic model developed from these data offers a highly robust meansto separate these two canine cancers. We demonstrated the use offluorescence in situ hybridization, using probes designed to detect andquantify regions of the canine genome and which are recurrently deletedin histiocytic malignancies, while being either minimally deleted incanine lymphoma, neutral in canine lymphoma, or increased in copy numberin canine lymphoma. We further demonstrated the use of digital dropletPCR, using Taq-Man® probes designed in a manner similar to those of thefluorescence in situ hybridization probes in the discrimination of LSAfrom HM.

The regions of the canine genome where assessment of DNA copy numbersignificantly differentiated canine lymphoma and histiocytic malignancywere subsequently evaluated for their ability to also discriminatebetween histiocytic malignancy and hemangiosarcoma, using DNA samplesisolated from a set of histopathologically verified cases of caninehemangiosarcoma.

Specifically, the disclosure provides a method to differentiate a caninehistiocytic malignancy from a lymphoma and from an hemangiosarcoma in abiological sample from a dog which comprises: (a) measuring a copynumber of dog chromosome (CFA) 2, CFA 16 and CFA 31 in the biologicalsample; (b) comparing the measured copy numbers to those of appropriatehistiocytic malignancy, hemangiosarcoma and lymphoma controls; and (c)if the copy numbers of CFA 2, CFA 16 and CFA 31 are reduced from that ofthe appropriate controls, determining that the dog has increasedlikelihood of presenting with an histiocytic malignancy rather than alymphoma or an hemangiosarcoma.

The copy number of the regions assessed may be measured by a variety ofanalytical approaches, including but not limited to the use offluorescence in situ hybridization (FISH), polymerase chain reaction(PCR), comparative genomic hybridization (CGH), or next generationsequencing.

The biological sample will be representative of the mass and may be atissue sample such as a tissue biopsy or fine needle aspirate, eitherintact or presented as a cytological smear, a fresh-frozen sample, afresh sample, or a formalin-fixed, paraffin-embedded (FFPE) sample.

The disclosure also provides a method of ruling out a dog for a lymphomatreatment wherein the dog may have a histiocytic malignancy or alymphoma which comprises: (a) measuring a copy number of CFA 2, CFA 16and CFA 31 in a biological sample from the dog; (b) comparing themeasured copy numbers to those of appropriate histiocytic malignancy andlymphoma controls; and (c) if the copy number of CFA 2, CFA 16 and CFA31 are reduced from that of appropriate controls, identifying the dog ashaving a histiocytic malignancy and ruling out a lymphoma treatment.

In addition, the disclosure provides a method of identifying a dog witha histiocytic malignancy treatment which comprises (a) measuring a copynumber of CFA 2, CFA 16 and CFA 31 in a biological sample from a dog;(b) comparing the measured copy numbers to those of appropriatehistiocytic malignancy and lymphoma controls; and (c) if the copy numberof CFA 2, CFA 16 and CFA 31 are reduced from that of the appropriatecontrols, identifying the dog with a histiocytic malignancy.

Also, the disclosure provides a kit for differentiating a histiocyticmalignancy from a lymphoma or an hemangiosarcoma in a dog comprising:(a) at least a plurality of reagents selected from the group consistingof: (i) a nucleic acid probe capable of specifically detecting CFA 2,CFA 16 and CFA 31; and (ii) instructions for use in measuring a copynumber of CFA 2, CFA 16 and CFA 31 in a biological sample from a dog;(b) wherein if the copy number of CFA 2, CFA 16 and CFA 31 are reducedfrom that of measured copy numbers for appropriate histiocyticmalignancy and lymphoma controls; and (c) determining that the dog hasincreased likelihood of a histiocytic malignancy rather than a lymphomaor hemangiosarcoma.

4. BRIEF DESCRIPTION OF THE FIGURES

FIG. 1. Validation of FISH probes used to detect and quantify threesegments of the canine genome, located on CFA 16 (segment 1), CFA 31(segment 3) and CFA 2 (segment 4), each of which are subject to highlyrecurrent copy number loss in histiocytic malignancies but not in caninelymphoma (as per table 1).

Panel A and B all three FISH probes, differentially labeled in (CFA 2,region 4, denoted by a triangle), (CFA 16, region 1, denoted by a star)and (CFA 31, region 3, denoted by an arrow), co-hybridized to ametaphase preparation and interphase nucleus from a healthy dog. In A)the dog chromosomes and nucleus are counterstained in DAPI, while in B)the image has been processed to reveal enhanced DAPI banding of thechromosome. It is clear from panels A and B that that all three probesmap to a single location on each pair of homologues of the correspondingdog chromosome, and have two discrete signals in the interphase nucleusshown in the top right of each image.

Panel C one homologue of each of CFA 2, 16 and 31 from panel B, enlargedand correctly oriented to demonstrate more precise chromosomal locationof the fluorescence signals. The Mb location (to two decimal places) ofthe canine genome sequence (reference to CanFam2) represented by eachprobe is shown to the right of the single homologues.

FIG. 2. Use of differential FISH probes to detect and quantify the threetarget segments of the canine genome from FIG. 1 [CFA 2 (segment 4,denoted by a triangle), CFA 16 (segment 1, denoted by a star) and CFA 31(segment 3, denoted by an arrow)], which are recurrently subject to copynumber loss in histiocytic malignancies and not in canine lymphomas. Allthree FISH probes are shown co-hybridized to a DAPI stained interphasenucleus from Panel A) a healthy dog and Panel B) group of DAPI stainedinterphase nuclei from a dog with confirmed histiocytic sarcoma.

Panel A—all three probes are seen as two discrete signals, shown withadjacent symbols (CFA 2=triangle, CFA 16=star, CFA 31=arrow) in Aii.Copy number recording for this cell would be represented as CFA 2=2, CFA16=2, CFA 31=2. A copy number of n=2 is considered normal for a diploidorganism.

Panel B—it is clear that not all signals are present as n=2. In Bii thesignal in five cells (labeled i-v) indicated with coded symbols(CFA2=triangle, CFA 16=star, CFA31=arrow) to indicate copy number asfollows: i) CFA 2=1, CFA 16=2, CFA 31=2. In cells ii-v the hybridizationscores are ii) CFA 2=1, CFA 16=2, CFA 31=2; iii) CFA 2=1, CFA 16=0, CFA31=1; iv) CFA 2=0, CFA 16=0, CFA 31=1; v) CFA 2=1, CFA 16=2, CFA 31=2.The mean copy number of each probe, based on these five cells, wouldthus be is CFA 2=2, CFA 16=1, CFA 1.6 and thus represent deletions ofall three segments evaluated, indicating that the cells have a targetedcopy number profile that is 1) inconsistent with the cells being deriveda lymphoma, and 2) consistent with the cells being derived from anhistiocytic neoplasm, as per the histologic diagnosis.

FIG. 3. Analysis of DNA copy number data indicated that segments 1, 3and 4, representing regions of CFA 16, 31 and 2 respectively, aresubject to recurrent copy number loss in canine histiocyticmalignancies, but not in canine lymphoma. Here an example is shown ofthe three probes CFA 2 (segment 4, denoted by a triangle), CFA 16(segment 1, denoted by a star) and CFA 31 (segment 3, denoted by anarrow)] used to detect and quantify their target segments of the caninegenome in DAPI stained interphase nuclei from a dog with ahistologically confirmed diagnosis of lymphoma. Panel A shows the rawdata and panel B includes symbols adjacent to each signal (CFA2=triangle, CFA 16=star, CFA 31=arrow) to indicate the signalsenumerated. In each case the copy number of the probe representing CFA 2(triangle) is are present as two copies (n=2), while in the lower of thethree cells the probes representing CFA 16 (star) and 31 (arrow) areboth present as three copies (n=3). These data are consistent with thecells being derived from a lymphoma and not a histiocytic neoplasm.

The recurrent decrease in copy number of these three regions of the doggenome in histiocytic malignancies, coinciding with a recurrent gain ofthe same regions in canine lymphoma allows detection and enumeration ofthese regions to provide a discriminatory assay between the twomalignancies.

FIG. 4. Droplet digital PCR based copy number results of a CFA 31 locusfor DNA samples isolated from tumor tissues of two cases of confirmedhemangiosarcoma (HEM 01-29 and HEM 02-30), two cases of confirmedlymphoma (LSA 01-80 and LSA 02-81), two cases of confirmed histiocyticmalignancy (HM 02-22 and 02-23). Also shown are the data for DNAisolated from tissue of a cancer free dog (control DNA) and also from aDNA/template free control (water). X-axis shows the samples and Y-axisshows the calculated copy number of the locus on CFA 31. The DNA copynumber of this locus in hemangiosarcoma and lymphoma cases is eitherneutral (same as control DNA) or increased (greater than that of the DNAcontrol), and in histiocytic malignancies it is generally reduced (belowthat of the DNA control).

FIG. 5. Image of the Receiver Operator Curve with area under the curveof 89.5% generated using an evaluation of segment 3 alone by dropletdigital PCR on 84 cases of hemangiosarcoma, 54 cases of histiocyticmalignancy, and 100 cases of lymphoma; all of which werehistopathologically confirmed. These data indicate the robustness of acopy number assay based on segment 3 alone via this platform, anddemonstrate a reduction to practice of this assay based on the digitaldroplet PCR assay for discrimination of histiocytic malignancy from bothlymphoma and hemagiosarcoma.

5. DETAILED DESCRIPTION OF THE INVENTION 5.1. Definitions

“Histiocytic malignancies” represent a spectrum of cancers. Histiocyticsarcomas are generally invasive (destroy the normal surrounding tissues)tumors that have a high rate of metastasis (spread to other areas of thebody). Histiocytic sarcoma that is restricted to one site of the body(localized histiocytic sarcoma) is generally found in the spleen, lymphnodes, bone marrow, skin, lung, brain, or limb joints. When histiocyticsarcoma is found at more than one anatomical site, the diagnosis becomesdisseminated histiocytic sarcoma, or malignant histiocytosis, both ofwhich are cancers that progress rapidly and generally involve multipleorgans simultaneously.

“Lymphoma” is a cancer caused by proliferation of lymphocytes, which arecells whose normal function is in the immune system. Dogs presentingwith lymphoma have variability in site(s) of involvement because thelymphocytes are located in numerous organs of the body. The most commonpresentation of canine lymphoma is an enlargement of one or more lymphnodes, which may be visible and/or palpated at the surface of the body.Lymphoma may also affect organs including spleen, liver and skin, aswell as the bone marrow, nervous system and gastrointestinal tract.

“Hemangiosarcoma” is a cancer that begins in the cells that line bloodvessels. These tumors are mainly located in the spleen, heart, or liver,although they can also been found in other regions of the body.Hemangiosarcoma is an indolent disease, but is almost always malignant.Since the cancer tends to develop slowly, but then spreads rapidly,affected dogs can remain without clinical signs until the tumors havemetastasized and/or ruptured. Once ruptured, the resulting internalbleeding can cause acute shock and death.

“Copy number” is a measurement of DNA, whether of a single locus, one ormore loci, or an entire genome. In all mammals (including the domesticdog) there are two types of cells, gametes (egg and sperm cells) andsomatic cells. The “wild-type”, or expected/normal copy number of eachlocus in the genome is expected to be one (n=1) in all gametes and two(n=2) in all somatic cells of females. In male cells all autosomes(non-sex chromosomes) in every somatic cell have a wild-type copy numberof n=2, but for the sex chromosomes (X and Y) each is present as onecopy. A “copy number” of other than two in a somatic cell of a dog(except for sex chromosomes in males) deviates from wild-type. Suchdeviations include ‘gains’, i.e., small increases in copy numbers (n>2),‘amplifications’, i.e. large increases in copy number, (generally n>5)and ‘losses’, i.e., decreases in copy numbers to n=1 or n=0.

“Labeled,” “labeled with a detectable label,” and “detectably labeled”are used interchangeably herein to indicate that an entity (e.g., aprobe) can be detected. “Label” and “detectable label” mean a moietyattached to an entity to render the entity detectable, such as a moietyattached to a probe to render the probe detectable upon binding to atarget sequence. The moiety, itself, may not be detectable but maybecome detectable upon reaction with yet another moiety. Use of the term“detectably labeled” is intended to encompass such labeling.

The detectable label can be selected such that the label generates asignal, which can be measured and the intensity of which is proportionalto the amount of bound entity. A wide variety of systems for labelingand/or detecting molecules, such as nucleic acids, e.g., probes, arewell-known. Labeled nucleic acids can be prepared by incorporating orconjugating a label that is directly or indirectly detectable byspectroscopic, photochemical, biochemical, immunochemical, electrical,optical, chemical or other means. Suitable detectable labels includeradioisotopes, fluorophores, chromophores, chemiluminescent agents,microparticles, enzymes, magnetic particles, electron dense particles,mass labels, spin labels, haptens, and the like. Fluorophores andchemiluminescent agents are preferred herein.

“Nucleic acid sample” refers to a sample comprising nucleic acid in aform suitable for hybridization with a probe, such as a samplecomprising nuclei or nucleic acids isolated or purified from suchnuclei. The nucleic acid sample may comprise total or partial (e.g.,particular chromosome(s)) genomic DNA, total or partial mRNA (e.g.,particular chromosome(s) or gene(s)), or selected sequence(s). Condensedchromosomes (such as are present in interphase or metaphase) aresuitable for use as targets in in situ hybridization, such as FISH.

“Predetermined cutoff” and “predetermined level” refer generally to acutoff value that is used to assess diagnostic/prognostic/therapeuticefficacy results by comparing the assay results against thepredetermined cutoff/level, where the predetermined cutoff/level alreadyhas been linked or associated with various clinical parameters (e.g.,severity of disease, progression/nonprogression/improvement, etc.).

“Probe,” in the context of the present disclosure may be a collection ofnucleic acid sequences, generally an oligonucleotide or polynucleotide,that can selectively hybridize to at least a portion of a targetsequence under conditions that allow for or promote selectivehybridization. In general, a probe can be complementary to the coding orsense (+) strand of DNA or complementary to the non-coding or anti-sense(−) strand of DNA (sometimes referred to as “reverse-complementary”).Probes can vary significantly in length. A length of about 10 to about100 nucleotides, such as about 15 to about 75 nucleotides, e.g., about15 to about 50 nucleotides, can be preferred in some applications suchas PCR, whereas a length of about 50 to about 1×10⁶ nucleotides can bepreferred for chromosomal probes and a length of about 5,000 to about800,000 nucleotides or more preferably about 100,000 to about 400,000for BAC probes. Probe may also refer to the use of a shortoligonucleotide that may contain a reporter molecule, such as but notlimited to TaqMan® probe, capable of being used to detecting andquantify the abundance of an amplicon.

The invention encompasses fragments of nucleic acids that can serve (1)as probes for detecting segments of domestic dog (Canis familairis, CFA)genome referred to as chromosomes 2, 16 and 31 (hereafter referred to asCFA 2, CFA 16 and CFA 31). The dog genome has been sequenced and isavailable for example, the NCBI Canis lupus familiaris genome database;ENSEMBL database CanFam3.1 (GCA_000002285.2) or the UCSC Genome Browserfor the Dog genome, Assembly: May 2005 (Broad/canFam2) or September 2011(Broad CanFam3.1/camFam3). See also, Lindblad-Toh et al. 2005 “Genomesequence, comparative analysis and haplotype structure of the domesticdog” Nature 438 (7069), 803-819.

The changes in copy number of loci located on any chromosome, includingbut not limited to CFA 2, 16 and 31, may be detected by a number ofmethods well known in the art, e.g. Southern and northern blotting, dotblotting, colony hybridizations, hybridization to an array, comparativegenomic hybridization (CGH), fluorescence in situ hybridization, etc. or(2) by a method using the polymerase chain reaction (PCR), including,but not limited to the use of short oligonucleotides as primers, each ofwhich are generally 15-30 bases in length and used to generate ampliconsfrom CFA 2, 16 and 31, for which the quantity or absolute amount of eachmay be determined, for example by comparison to the amount of anamplicon generated from a stable/copy number neutral/balanced region ofthe genome (where copy number per cell is n=2), as a means to calculateany deviation from a copy number of n=2 in the nucleic acid sample beingevaluated. An example of this would be the use of quantitative PCR ordroplet digital PCR. In these examples, an additional oligonucleotidemay be included to represent a “probe”, such as, but not limited to, forexample TaqMan® MGB assays suitable for use in DNA copy number analysis.PCR primers can comprise, in addition to CFA 2, 16 and 31 nucleic acidsequences, other sequences such as restriction enzyme cleavage sitesthat facilitate the use of the amplified nucleic acid. PCR is describedin the following references: Saiki et al. 1988 Science 239 487-491; PCRTechnology, Erlich, ed., Stockton Press, (1989). As explained below, PCRcan be useful to detect changes in the levels of CFA 2, 16 and 31.

Hybridization techniques are well known in the art and are described bySambrook, J., E. F. Fritsch, and T. Maniatis (Molecular Cloning: ALaboratory Manual, Cold Spring Harbor Laboratory Press, Cold SpringHarbor, N.Y., chapters 9 and 11, (1989)) and Current Protocols inMolecular Biology (F. M. Ausubel et al., eds., John Wiley & Sons, Inc.,sections 2.10 and 6.3-6.4 (1995)), the relevant portions of which areincorporated by reference herein. Moderately stringent conditions forfilter hybridizations include hybridization in about 50% formamide,6×SSC at a temperature from about 42 C to 55 C and washing at about 60 Cin 0.5×SSC, 0.1% SDS. Highly stringent conditions are defined ashybridization conditions as above, but with washing at approximately 68C in 0.2×SSC, 0.1% SDS. SSPE (1×SSPE is 0.15 M NaCl, 10 mM NaH₂PO₄, and1.26 mM EDTA, pH 7.4) can be substituted for SSC (1×SSC is 0.15 M NaCland 15 mM sodium citrate) in the hybridization and wash buffers; washes,optionally at least two washes, are performed for 15 minutes afterhybridization is complete.

It should be understood that the wash temperature and wash saltconcentration can be adjusted as necessary to achieve a desired degreeof stringency by applying the basic principles that govern hybridizationreactions and duplex stability, as known to those skilled in the art anddescribed further below (see e.g., Sambrook et al., supra). When nucleicacids of known sequence are hybridized, the hybrid length can bedetermined by aligning the sequences of the nucleic acids (for example,using BLAST or a variant) and identifying the region or regions ofoptimal sequence complementarity. The hybridization temperature forhybrids anticipated to be less than 50 base pairs in length should be 5to 10° C. less than the melting temperature (Tm) of the hybrid, where Tmis determined according to the following equations. For hybrids lessthan 18 base pairs in length, Tm (degrees C.)=2(# of A+T bases)+4(# ofG+C bases). For hybrids greater than 18 base pairs in length, Tm(degrees C.)=81.5+16.6(log₁₀[Na+])+0.41 (% G+C)−(600 N), where N is thenumber of bases in the hybrid, and [Na+] is the concentration of sodiumions in the hybridization buffer. Each such hybridizing nucleic acid hasa length that is at least 15 nucleotides (or at least 18 nucleotides, orat least 20, or at least 25, or at least 30, or at least 40, or at least50, or at least 100. Sambrook et al., supra.

5.2. Polynucleotide Amplification and Determination

In many instances, it is desirable to amplify a nucleic acid sequenceusing any of several nucleic acid amplification procedures that are wellknown in the art. Specifically, nucleic acid amplification is thechemical or enzymatic synthesis of nucleic acid copies that contain asequence complementary to a nucleic acid sequence being amplified(template). The methods and kits of the invention may use any nucleicacid amplification or detection methods known to one skilled in the art,such as those described in U.S. Pat. No. 5,525,462 (Takarada et al.);U.S. Pat. No. 6,114,117 (Hepp et al.); U.S. Pat. No. 6,127,120 (Grahamet al.); U.S. Pat. No. 6,344,317 (Urnovitz); U.S. Pat. No. 6,448,001(Oku); U.S. Pat. No. 6,528,632 (Catanzariti et al.); and PCT Pub. No. WO2005/111209 (Nakajima et al.); all of which are incorporated herein byreference in their entirety.

Commonly used methods known in the art for the quantification of mRNAexpression in a sample include northern blotting and in situhybridization (Parker and Barnes, Methods Mol. Biol. 106:247-83, 1999),RNAse protection assays (Hod, Biotechniques 13:852-54, 1992), PCR-basedmethods, such as reverse transcription PCR (RT-PCR) (Weis et al., TIG8:263-64, 1992), and array-based methods (Schena et al., Science270:467-70, 1995). Alternatively, antibodies may be employed that canrecognize specific duplexes, including DNA duplexes, RNA duplexes, andDNA-RNA hybrid duplexes, or DNA-protein duplexes. Representative methodsfor sequencing-based gene expression analysis include Serial Analysis ofGene Expression (SAGE), bead-based technologies, single moleculefluorescence in situ hybridization (smFISH) studies, and gene expressionanalysis by massively parallel signature sequencing. Velculescu et al.1995 Science 270 484-487; Streefkerk et al., 1976, Pro Biol Fluid ProcColl 24 811-814; U.S. Pat. No. 5,028,545 (Soini); smFISH, Lyubimova etal. 2013 Nat Protocol 8(9) 1743-1758.

In some embodiments, the nucleic acids are amplified by PCRamplification using methodologies known to one skilled in the art. Oneskilled in the art will recognize, however, that amplification can beaccomplished by any known method, such as ligase chain reaction (LCR),Qβ-replicase amplification, rolling circle amplification, transcriptionamplification, self-sustained sequence replication, nucleic acidsequence-based amplification (NASBA), each of which provides sufficientamplification. Branched-DNA technology may also be used to qualitativelydemonstrate the presence of a sequence of the technology, whichrepresents a particular methylation pattern, or to quantitativelydetermine the amount of this particular genomic sequence in a sample.Nolte reviews branched-DNA signal amplification for direct quantitationof nucleic acid sequences in clinical samples (Nolte, 1998, Adv. Clin.Chem. 33:201-235).

The PCR process is well known in the art and is thus not described indetail herein. For a review of PCR methods and protocols, see, e.g.,Innis et al., eds., PCR Protocols, A Guide to Methods and Application,Academic Press, Inc., San Diego, Calif. 1990; U.S. Pat. No. 4,683,202(Mullis); which are incorporated herein by reference in their entirety.PCR reagents and protocols are also available from commercial vendors,such as Roche Molecular Systems. PCR may be carried out as an automatedprocess with a thermostable enzyme. In this process, the temperature ofthe reaction mixture is cycled through a denaturing region, a primerannealing region, and an extension reaction region automatically.Machines specifically adapted for this purpose are commerciallyavailable.

5.3. High Throughput, Single Molecule Sequencing, and Direct DetectionTechnologies

Suitable next generation sequencing technologies are widely available.Examples include the 454 Life Sciences platform (Roche, Branford, Conn.)(Margulies et al. 2005 Nature, 437, 376-380); Illumina's GenomeAnalyzer, GoldenGate Methylation Assay, or Infinium Methylation Assays,i.e., Infinium HumanMethylation 27K BeadArray or VeraCode GoldenGatemethylation array (Illumina, San Diego, Calif.; Bibkova et al., 2006,Genome Res. 16, 383-393; U.S. Pat. Nos. 6,306,597 and 7,598,035(Macevicz); U.S. Pat. No. 7,232,656 (Balasubramanian et al.)); or DNASequencing by Ligation, SOLiD System (Applied Biosystems/LifeTechnologies; U.S. Pat. Nos. 6,797,470, 7,083,917, 7,166,434, 7,320,865,7,332,285, 7,364,858, and 7,429,453 (Barany et al.); or the Helicos TrueSingle Molecule DNA sequencing technology (Harris et al., 2008 Science,320, 106-109; U.S. Pat. Nos. 7,037,687 and 7,645,596 (Williams et al.);U.S. Pat. No. 7,169,560 (Lapidus et al.); U.S. Pat. No. 7,769,400(Harris)), the single molecule, real-time (SMRT™) technology of PacificBiosciences, and sequencing (Soni and Meller, 2007, Clin. Chem. 53,1996-2001) which are incorporated herein by reference in their entirety.These systems allow the sequencing of many nucleic acid moleculesisolated from a specimen at high orders of multiplexing in a parallelfashion (Dear, 2003, Brief Funct. Genomic Proteomic, 1(4), 397-416 andMcCaughan and Dear, 2010, J. Pathol., 220, 297-306). Each of theseplatforms allow for sequencing of clonally expanded or non-amplifiedsingle molecules of nucleic acid fragments. Certain platforms involve,for example, (i) sequencing by ligation of dye-modified probes(including cyclic ligation and cleavage), (ii) pyrosequencing, and (iii)single-molecule sequencing.

Pyrosequencing is a nucleic acid sequencing method based on sequencingby synthesis, which relies on detection of a pyrophosphate released onnucleotide incorporation. Generally, sequencing by synthesis involvessynthesizing, one nucleotide at a time, a DNA strand complimentary tothe strand whose sequence is being sought. Nucleic acids may beimmobilized to a solid support, hybridized with a sequencing primer,incubated with DNA polymerase, ATP sulfurylase, luciferase, apyrase,adenosine 5′ phosphosulfate and luciferin. Nucleotide solutions aresequentially added and removed. Correct incorporation of a nucleotidereleases a pyrophosphate, which interacts with ATP sulfurylase andproduces ATP in the presence of adenosine 5′ phosphosulfate, fueling theluciferin reaction, which produces a chemiluminescent signal allowingsequence determination. Machines for pyrosequencing and methylationspecific reagents are available from Qiagen, Inc. (Valencia, Calif.).See also Tost and Gut, 2007, Nat. Prot. 2 2265-2275. An example of asystem that can be used by a person of ordinary skill based onpyrosequencing generally involves the following steps: ligating anadaptor nucleic acid to a study nucleic acid and hybridizing the studynucleic acid to a bead; amplifying a nucleotide sequence in the studynucleic acid in an emulsion; sorting beads using a picoliter multiwellsolid support; and sequencing amplified nucleotide sequences bypyrosequencing methodology (e.g., Nakano et al., 2003, J. Biotech. 102,117-124). Such a system can be used to exponentially amplifyamplification products generated by a process described herein, e.g., byligating a heterologous nucleic acid to the first amplification productgenerated by a process described herein.

Certain single-molecule sequencing aspects are based on the principal ofsequencing by synthesis, and utilize single-pair Fluorescence ResonanceEnergy Transfer (single pair FRET) as a mechanism by which photons areemitted as a result of successful nucleotide incorporation. The emittedphotons often are detected using intensified or high sensitivity cooledcharge-couple-devices in conjunction with total internal reflectionmicroscopy (TIRM). Photons are only emitted when the introduced reactionsolution contains the correct nucleotide for incorporation into thegrowing nucleic acid chain that is synthesized as a result of thesequencing process. In FRET-based single-molecule sequencing ordetection, energy is transferred between two fluorescent dyes, sometimespolymethine cyanine dyes Cy3 and Cy5, through long-range dipoleinteractions. The donor is excited at its specific excitation wavelengthand the excited state energy is transferred, non-radiatively to theacceptor dye, which in turn becomes excited. The acceptor dye eventuallyreturns to the ground state by radiative emission of a photon. The twodyes used in the energy transfer process represent the “single pair”, insingle pair FRET. Cy3 often is used as the donor fluorophore and oftenis incorporated as the first labeled nucleotide. Cy5 often is used asthe acceptor fluorophore and is used as the nucleotide label forsuccessive nucleotide additions after incorporation of a first Cy3labeled nucleotide. The fluorophores generally are within 10 nanometersof each other for energy transfer to occur successfully. Bailey et al.recently reported a highly sensitive (15 pg methylated DNA) method usingquantum dots to detect methylation status using fluorescence resonanceenergy transfer (MS-qFRET)(Bailey et al. 2009, Genome Res. 19(8),1455-1461, which is incorporated herein by reference in its entirety).

An example of a system that can be used based on single-moleculesequencing generally involves hybridizing a primer to a study nucleicacid to generate a complex; associating the complex with a solid phase;iteratively extending the primer by a nucleotide tagged with afluorescent molecule; and capturing an image of fluorescence resonanceenergy transfer signals after each iteration (e.g., Braslavsky et al.,PNAS 100(7): 3960-3964 (2003); U.S. Pat. No. 7,297,518 (Quake et al.)which are incorporated herein by reference in their entirety). Such asystem can be used to directly sequence amplification products generatedby processes described herein. In some embodiments the released linearamplification product can be hybridized to a primer that containssequences complementary to immobilized capture sequences present on asolid support, a bead or glass slide for example. Hybridization of theprimer-released linear amplification product complexes with theimmobilized capture sequences, immobilizes released linear amplificationproducts to solid supports for single pair FRET-based sequencing bysynthesis. The primer often is fluorescent, so that an initial referenceimage of the surface of the slide with immobilized nucleic acids can begenerated. The initial reference image is useful for determininglocations at which true nucleotide incorporation is occurring.Fluorescence signals detected in array locations not initiallyidentified in the “primer only” reference image are discarded asnon-specific fluorescence. Following immobilization of theprimer-released linear amplification product complexes, the boundnucleic acids often are sequenced in parallel by the iterative steps of,a) polymerase extension in the presence of one fluorescently labelednucleotide, b) detection of fluorescence using appropriate microscopy,TIRM for example, c) removal of fluorescent nucleotide, and d) return tostep (a) with a different fluorescently labeled nucleotide.

The technology may be practiced with digital PCR. Digital PCR wasdeveloped by Kalinina and colleagues (Kalinina et al., 1997, NucleicAcids Res. 25; 1999-2004) and further developed by Vogelstein andKinzler (1999, Proc. Natl. Acad. Sci. U.S.A. 96; 9236-9241). Theapplication of digital PCR is described by Cantor et al. (PCT Pub. Nos.WO 2005/023091A2 (Cantor et al.); WO 2007/092473 A2, (Quake et al.)),which are hereby incorporated by reference in their entirety. DigitalPCR takes advantage of nucleic acid (DNA, cDNA or RNA) amplification ona single molecule level, and offers a highly sensitive method forquantifying low copy number nucleic acids. Fluidigm® Corporation,BioRad's Digital PCR and Raindance technologies all offer systems forthe digital analysis of nucleic acids. See, Karlin-Neumann G et al.(2012). Probing copy number variations using Bio-Rad's QX100™ DropletDigital™ PCR system. Bio-Rad Bulletin 6277; Diderot et al., ClinicalChemistry February 2013 clinchem.2012.193409.

In some embodiments, nucleotide sequencing may be by solid phase singlenucleotide sequencing methods and processes. Solid phase singlenucleotide sequencing methods involve contacting sample nucleic acidsand a solid support under conditions in which a single molecule ofsample nucleic acid hybridizes to a single molecule of a solid support.Such conditions can include providing the solid support molecules and asingle molecule of sample nucleic acid in a “microreactor.” Suchconditions also can include providing a mixture in which the samplenucleic acid molecule can hybridize to solid phase nucleic acid on thesolid support. Single nucleotide sequencing methods useful in theembodiments described herein are described in PCT Pub. No. WO2009/091934 (Cantor).

In certain embodiments, nanopore sequencing detection methods include(a) contacting a nucleic acid for sequencing (“base nucleic acid,” e.g.,linked probe molecule) with sequence-specific detectors, underconditions in which the detectors specifically hybridize tosubstantially complementary subsequences of the base nucleic acid; (b)detecting signals from the detectors; and (c) determining the sequenceof the base nucleic acid according to the signals detected. In certainembodiments, the detectors hybridized to the base nucleic acid aredisassociated from the base nucleic acid (e.g., sequentiallydissociated) when the detectors interfere with a nanopore structure asthe base nucleic acid passes through a pore, and the detectorsdisassociated from the base sequence are detected.

A detector also may include one or more regions of nucleotides that donot hybridize to the base nucleic acid. In some embodiments, a detectoris a molecular beacon. A detector often comprises one or more detectablelabels independently selected from those described herein. Eachdetectable label can be detected by any convenient detection processcapable of detecting a signal generated by each label (e.g., magnetic,electric, chemical, optical and the like). For example, a CD camera canbe used to detect signals from one or more distinguishable quantum dotslinked to a detector.

Next generation sequencing techniques may be applied to measureexpression levels or count numbers of transcripts using RNA-seq or wholetranscriptome shotgun sequencing. See, e.g., Mortazavi et al. 2008 NatMeth 5(7) 621-627; or Wang et al. 2009 Nat Rev Genet 10(1) 57-63.

Nucleic acids in the invention may be counted using methods known in theart. In one embodiment, NanoString's nCounter system may be used. Geisset al. 2008 Nat Biotech 26(3) 317-325; U.S. Pat. No. 7,473,767(Dimitrov). Alternatively, Fluidigm's Dynamic Array system may be used.Byrne et al. 2009 PLoS ONE 4 e7118; Helzer et al. 2009 Can Res 697860-7866. For reviews, see also Zhao et al. 2011 Sci China Chem 54(8)1185-1201; and Ozsolak and Milos 2011 Nat Rev Genet 12 87-98.

The invention encompasses any method known in the art for enhancing thesensitivity of the detectable signal in such assays, including, but notlimited to, the use of cyclic probe technology (Bakkaoui et al., 1996,BioTechniques 20: 240-8, which is incorporated herein by reference inits entirety); and the use of branched probes (Urdea et al., 1993, Clin.Chem. 39, 725-6; which is incorporated herein by reference in itsentirety). The hybridization complexes are detected according towell-known techniques in the art.

Reverse transcribed or amplified nucleic acids may be modified nucleicacids. Modified nucleic acids can include nucleotide analogs, and incertain embodiments include a detectable label and/or a capture agent.Examples of detectable labels include, without limitation, fluorophores,radioisotopes, colorimetric agents, light emitting agents,chemiluminescent agents, light scattering agents, enzymes and the like.Examples of capture agents include, without limitation, an agent from abinding pair selected from antibody/antigen, antibody/antibody,antibody/antibody fragment, antibody/antibody receptor, antibody/proteinA or protein G, hapten/anti-hapten, biotin/avidin, biotin/streptavidin,folic acid/folate binding protein, vitamin B12/intrinsic factor,chemical reactive group/complementary chemical reactive group (e.g.,sulfhydryl/maleimide, sulfhydryl/haloacetyl derivative,amine/isotriocyanate, amine/succinimidyl ester, and amine/sulfonylhalides) pairs, and the like. Modified nucleic acids having a captureagent can be immobilized to a solid support in certain embodiments.

The invention described herein may be used in conjunction with othermolecular techniques for detection of cancer such as US Pat Pub2013/0171637 (Giafis et al.) the contents of which are herebyincorporated by reference in its entirety.

5.4. Statistical Methods

The data may be ranked for its ability to distinguish biomarkers in boththe 1 versus all (i.e., disease versus normal) and the all-pairwise(i.e., normal versus specific disease) cases. One statistic used for theranking is the area under the receiver operator characteristic (ROC)curve (a plot of sensitivity versus (1-specificity)). Althoughbiomarkers are evaluated for reliability across datasets, theindependent sample sets are not combined for the purposes of the ROCranking. As a result, multiple independent analyses are performed andmultiple independent rankings are obtained for each biomarker's abilityto distinguish groups of interest.

It is to be understood that other genes and/or diagnostic criteria maybe used in this invention. For example, animal signs, standard bloodworkups, the results of imaging tests, and/or histological evaluationmay optionally be combined with biomarkers disclosed herein.

Such analysis methods may be used to form a predictive model, and thenuse that model to classify test data. For example, one convenient andparticularly effective method of classification employs multivariatestatistical analysis modeling, first to form a model (a “predictivemathematical model”) using data (“modeling data”) from samples of knownclass (e.g., from subjects known to have, or not have, a particularclass, subclass or grade of lung cancer), and second to classify anunknown sample (e.g., “test data”), according to lung cancer status.

Pattern recognition (PR) methods have been used widely to characterizemany different types of problems ranging for example over linguistics,fingerprinting, chemistry and psychology. In the context of the methodsdescribed herein, pattern recognition is the use of multivariatestatistics, both parametric and non-parametric, to analyze spectroscopicdata, and hence to classify samples and to predict the value of somedependent variable based on a range of observed measurements. There aretwo main approaches. One set of methods is termed “unsupervised” andthese simply reduce data complexity in a rational way and also producedisplay plots that can be interpreted by the human eye. The otherapproach is termed “supervised” whereby a training set of samples withknown class or outcome is used to produce a mathematical model and isthen evaluated with independent validation data sets.

Unsupervised PR methods are used to analyze data without reference toany other independent knowledge. Examples of unsupervised patternrecognition methods include principal component analysis (PCA),hierarchical cluster analysis (HCA), and non-linear mapping (NLM).

Alternatively, and in order to develop automatic classification methods,it has proved efficient to use a “supervised” approach to data analysis.Here, a “training set” of biomarker data is used to construct astatistical model that predicts correctly the “class” of each sample.This training set is then tested with independent data (referred to as atest or validation set) to determine the robustness of thecomputer-based model. These models are sometimes termed “expertsystems,” but may be based on a range of different mathematicalprocedures. Supervised methods can use a data set with reduceddimensionality (for example, the first few principal components), buttypically use unreduced data, with all dimensionality. In all cases themethods allow the quantitative description of the multivariateboundaries that characterize and separate each class, for example, eachclass of lung cancer in terms of its biomarker expression profile. It isalso possible to obtain confidence limits on any predictions, forexample, a level of probability to be placed on the goodness of fit(see, for example, Sharaf; Illman; Kowalski, eds. (1986). Chemometrics.New York: Wiley). The robustness of the predictive models can also bechecked using cross-validation, by leaving out selected samples from theanalysis.

Examples of supervised pattern recognition methods include the followingnearest centroid methods (Dabney 2005 Bioinformatics 21(22):4148-4154and Tibshirani et al. 2002 Proc. Natl. Acad. Sci. USA 99(10):6576-6572);soft independent modeling of class analysis (SIMCA) (see, for example,Wold, (1977) Chemometrics: theory and application 52: 243-282.); partialleast squares analysis (PLS) (see, for example, Wold (1966) Multivariateanalysis 1: 391-420; Joreskog (1982) Causality, structure, prediction 1:263-270); linear discriminant analysis (LDA) (see, for example, Nillson(1965). Learning machines. New York.); K-nearest neighbor analysis (KNN)(see, for example, Brown and Martin 1996 J Chem Info Computer Sci36(3):572-584); artificial neural networks (ANN) (see, for example,Wasserman (1993). Advanced methods in neural computing. John Wiley &Sons, Inc; O'Hare & Jennings (Eds.). (1996). Foundations of distributedartificial intelligence (Vol. 9). Wiley); probabilistic neural networks(PNNs) (see, for example, Bishop & Nasrabadi (2006). Pattern recognitionand machine learning (Vol. 1, p. 740). New York: Springer; Specht,(1990). Probabilistic neural networks. Neural networks, 3(1), 109-118);rule induction (RI) (see, for example, Quinlan (1986) Machine learning,1(1), 81-106); and, Bayesian methods (see, for example, Bretthorst(1990). An introduction to parameter estimation using Bayesianprobability theory. In Maximum entropy and Bayesian methods (pp. 53-79).Springer Netherlands; Bretthorst, G. L. (1988). Bayesian spectrumanalysis and parameter estimation (Vol. 48). New York: Springer-Verlag);unsupervised hierarchical clustering (see for example Herrero 2001Bioinformatics 17(2) 126-136). In one embodiment, the classifier is thecentroid based method described in Mullins et al. 2007 Clin Chem53(7):1273-9, which is herein incorporated by reference in its entiretyfor its teachings regarding disease classification.

It is often useful to pre-process data, for example, by addressingmissing data, translation, scaling, weighting, etc. Multivariateprojection methods, such as principal component analysis (PCA) andpartial least squares analysis (PLS), are so-called scaling sensitivemethods. By using prior knowledge and experience about the type of datastudied, the quality of the data prior to multivariate modeling can beenhanced by scaling and/or weighting. Adequate scaling and/or weightingcan reveal important and interesting variation hidden within the data,and therefore make subsequent multivariate modeling more efficient.Scaling and weighting may be used to place the data in the correctmetric, based on knowledge and experience of the studied system, andtherefore reveal patterns already inherently present in the data.

If possible, missing data, for example gaps in column values, should beavoided. However, if necessary, such missing data may replaced or“filled” with, for example, the mean value of a column (“mean fill”); arandom value (“random fill”); or a value based on a principal componentanalysis (“principal component fill”). Each of these differentapproaches will have a different effect on subsequent PR analysis.

“Translation” of the descriptor coordinate axes can be useful. Examplesof such translation include normalization and mean centering.“Normalization” may be used to remove sample-to-sample variation. Manynormalization approaches are possible, and they can often be applied atany of several points in the analysis. “Mean centering” may be used tosimplify interpretation. Usually, for each descriptor, the average valueof that descriptor for all samples is subtracted. In this way, the meanof a descriptor coincides with the origin, and all descriptors are“centered” at zero. In “unit variance scaling,” data can be scaled toequal variance. Usually, the value of each descriptor is scaled by1/StDev, where StDev is the standard deviation for that descriptor forall samples. “Pareto scaling” is, in some sense, intermediate betweenmean centering and unit variance scaling. In pareto scaling, the valueof each descriptor is scaled by 1/sqrt(StDev), where StDev is thestandard deviation for that descriptor for all samples. In this way,each descriptor has a variance numerically equal to its initial standarddeviation. The pareto scaling may be performed, for example, on raw dataor mean centered data.

“Logarithmic scaling” may be used to assist interpretation when datahave a positive skew and/or when data spans a large range, e.g., severalorders of magnitude. Usually, for each descriptor, the value is replacedby the logarithm of that value. In “equal range scaling,” eachdescriptor is divided by the range of that descriptor for all samples.In this way, all descriptors have the same range, that is, 1. However,this method is sensitive to presence of outlier points. In“autoscaling,” each data vector is mean centred and unit variancescaled. This technique is a very useful because each descriptor is thenweighted equally and large and small values are treated with equalemphasis. This can be important for analytes present at very low, butstill detectable, levels.

Several supervised methods of scaling data are also known. Some of thesecan provide a measure of the ability of a parameter (e.g., a descriptor)to discriminate between classes, and can be used to improveclassification by stretching a separation. For example, in “varianceweighting,” the variance weight of a single parameter (e.g., adescriptor) is calculated as the ratio of the inter-class variances tothe sum of the intra-class variances. A large value means that thisvariable is discriminating between the classes. For example, if thesamples are known to fall into two classes (e.g., a training set), it ispossible to examine the mean and variance of each descriptor. If adescriptor has very different mean values and a small variance, then itwill be good at separating the classes. “Feature weighting” is a moregeneral description of variance weighting, where not only the mean andstandard deviation of each descriptor is calculated, but otherwell-known weighting factors, such as the Fisher weight, are used.

The methods described herein may be implemented and/or the resultsrecorded using any device capable of implementing the methods and/orrecording the results. Examples of devices that may be used include butare not limited to electronic computational devices, including computersof all types. When the methods described herein are implemented and/orrecorded in a computer, the computer program that may be used toconfigure the computer to carry out the steps of the methods may becontained in any computer readable medium capable of containing thecomputer program. Examples of computer readable medium that may be usedinclude but are not limited to diskettes, CD-ROMs, DVDs, ROM, RAM, andother memory and computer storage devices. The computer program that maybe used to configure the computer to carry out the steps of the methodsand/or record the results may also be provided over an electronicnetwork, for example, over the internet, an intranet, or other network.

The process of comparing a measured value and a reference value can becarried out in any convenient manner appropriate to the type of measuredvalue and reference value for the discriminative gene at issue.“Measuring” can be performed using quantitative or qualitativemeasurement techniques, and the mode of comparing a measured value and areference value can vary depending on the measurement technologyemployed. For example, when a qualitative colorimetric assay is used tomeasure expression levels, the levels may be compared by visuallycomparing the intensity of the colored reaction product, or by comparingdata from densitometric or spectrometric measurements of the coloredreaction product (e.g., comparing numerical data or graphical data, suchas bar charts, derived from the measuring device). However, it isexpected that the measured values used in the methods of the inventionwill most commonly be quantitative values. In other examples, measuredvalues are qualitative. As with qualitative measurements, the comparisoncan be made by inspecting the numerical data, or by inspectingrepresentations of the data (e.g., inspecting graphical representationssuch as bar or line graphs).

The process of comparing may be manual (such as visual inspection by thepractitioner of the method) or it may be automated. For example, anassay device (such as a luminometer for measuring chemiluminescentsignals) may include circuitry and software enabling it to compare ameasured value with a reference value for a biomarker. Alternately, aseparate device (e.g., a digital computer) may be used to compare themeasured value(s) and the reference value(s). Automated devices forcomparison may include stored reference values for the biomarker beingmeasured, or they may compare the measured value(s) with referencevalues that are derived from contemporaneously measured referencesamples (e.g., samples from control subjects).

As will be apparent to those of skill in the art, when replicatemeasurements are taken, the measured value that is compared with thereference value is a value that takes into account the replicatemeasurements. The replicate measurements may be taken into account byusing either the mean or median of the measured values as the “measuredvalue.”

The invention also includes methods of identifying animals forparticular treatments or selecting animals for which a particulartreatment would be desirable or contraindicated.

The methods above may be performed by a reference laboratory, aveterinary hospital pathology laboratory, a university veterinarylaboratory, a veterinarian's office or a veterinarian. The methods abovemay further comprise an algorithm and/or statistical analysis.

5.5. Samples

The sample may be a blood, saliva, stool, tissue, or urine sampleprovided the sample contains cells of the neoplasm. Preferably the cellor cells will be obtained directly from a suspected neoplastic mass,including but not limited to lymph nodes. For the cytogenetic assays, asshown in the examples, cells are used to provide templates for the FISHprobes. For PCR assays, tumor DNA may be obtained from cells or anucleic acid extraction from cells. The sample may be obtained from anycollection of tissues, or bodily fluids containing cells in whichbiomarker(s) can be detected. Examples of such samples include, but arenot limited to, biopsies and smears. Bodily fluids useful in the presentinvention include blood, lymph, urine, saliva, nipple aspirates,gynecological fluids, or any other bodily secretion or derivativethereof. Blood can include whole blood, plasma, serum, or any derivativeof blood containing cells. Body samples may be obtained from a patientby a variety of techniques including, for example, by scraping orswabbing an area, by using a needle to aspirate cells or bodily fluids,or by removing a tissue sample (i.e., biopsy). In some embodiments, thesample may be obtained from a tissue from a biopsy, such as a wedge,needle biopsy or excisional biopsy. Methods for collecting various bodysamples are well known in the art. Fixative and staining solutions maybe applied to the cells or tissues for preserving the specimen and forfacilitating examination. Samples, particularly tumor tissue samples,may be transferred to a glass slide for viewing under magnification. Inone embodiment, the body sample is a formalin-fixed, paraffin-embedded(FFPE) tissue sample.

5.6. Compositions and Kits

The invention provides compositions and kits for distinguishinghistiocytic malignancy from lymphoma in a dog comprising: (a) at leastone reagent selected from the group consisting of: a plurality ofnucleic acid probes capable of specifically detecting CFA 2, CFA 16 andCFA 31; and (b) instructions for use in measuring a copy number of CFA2, CFA 16 and CFA 31 in a biological sample from a dog wherein if thecopy number of CFA 2 and/or CFA 16 and/or CFA 31 in cells from the dogsample are <2 determining the dog has an increased likelihood of havinga histiocytic malignancy rather than a lymphoma or hemangiosarcoma.

The instructions comprise determining in a sample of relevant cellsobtained from the dog the presence of chromosomal abnormalities, whereinthe presence of chromosomal abnormalities involving at least two of theprobes indicates that the patient has a particular cancer. Such kits mayfurther comprise, or consist of, blocking agents or other probes,various labels or labeling agents to facilitate detection of the probes,reagents for hybridization (e.g., buffers), a metaphase spread, and thelike.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. The article “a” and “an” areused herein to refer to one or more than one (i.e., to at least one) ofthe grammatical object(s) of the article. By way of example, “anelement” means one or more elements.

Throughout the specification the word “comprising,” or variations suchas “comprises” or “comprising,” will be understood to imply theinclusion of a stated element, integer or step, or group of elements,integers or steps, but not the exclusion of any other element, integeror step, or group of elements, integers or steps. The present inventionmay suitably “comprise”, “consist of”, or “consist essentially of”, thesteps, elements, and/or reagents described in the claims.

It is further noted that the claims may be drafted to exclude anyoptional element. As such, this statement is intended to serve asantecedent basis for use of such exclusive terminology as “solely”,“only” and the like in connection with the recitation of claim elements,or the use of a “negative” limitation.

Where a range of values is provided, it is understood that eachintervening value, to the tenth of the unit of the lower limit unlessthe context clearly dictates otherwise, between the upper and lowerlimits of that range is also specifically disclosed. Each smaller rangebetween any stated value or intervening value in a stated range and anyother stated or intervening value in that stated range is encompassedwithin the invention. The upper and lower limits of these smaller rangesmay independently be included or excluded in the range, and each rangewhere either, neither or both limits are included in the smaller rangesis also encompassed within the invention, subject to any specificallyexcluded limit in the stated range. Where the stated range includes oneor both of the limits, ranges excluding either or both of those includedlimits are also included in the invention.

The following Examples further illustrate the invention and are notintended to limit the scope of the invention. In particular, it is to beunderstood that this invention is not limited to particular embodimentsdescribed, as such may, of course, vary. It is also to be understoodthat the terminology used herein is for the purpose of describingparticular embodiments only, and is not intended to be limiting, sincethe scope of the present invention will be limited only by the appendedclaims.

6. EXAMPLES 6.1. Experimental Data

Tumor biopsy samples were obtained from 101 dogs with a confirmeddiagnosis of lymphoma, and 44 dogs with a confirmed diagnosis of ahistiocytic neoplasm. Genomic DNA was isolated from all 145 tumorbiopsies and each was used to generate a genome wide DNA copy profile,using a comparative genomic hybridization array comprising 180,000unique 60-mer oligonucleotide probes at ˜13.5 kb mean spacing throughoutthe canine genome (ID#25522, Agilent Technologies). All procedures usedto generate these data have been reported previously by the inventor'slaboratory (Thomas et al., 2011, Hedan et al., 2011, Angstadt et al.,2012).

Following hybridization, each array was scanned at 3 μm resolution usingan Agilent G2565CA DNA Microarray Scanner with SureScan High resolutiontechnology (Agilent Technologies). Scan data were assessed for dataquality by the ‘Quality Metrics’ report in Agilent's Feature extractionsoftware (v10.5)(Agilent Technologies). FASST2 Segmentation Algorithm, aHidden Markov Model (HMM) based approach, was used to make copy numbercalls. The FASST2 algorithm, unlike other common HMM methods for copynumber estimation, does not aim to estimate the copy number state ateach probe but uses many states to cover more possibilities, such asmosaic events. These state values are then used to make calls based on alog-ratio threshold. The significance threshold for segmentation was setat 5×10⁻⁶, also requiring a minimum of three probes per segment and amaximum probe spacing of 1 Mb between adjacent probes before breaking asegment. The log ratio thresholds for single copy gain and single copyloss were set at +0.2 and −0.23, respectively.

DNA copy number aberrations ‘called’ by the FASST2 segmentationalgorithm were compared across the cohorts of histiocytic malignancies(group A) and lymphoma (group B) to identify those that hadsignificantly different frequencies between the cancer types. The fulllengths of chromosomes 2, 16 and 31 were the top three chromosomes toshow differential copy number status when comparing canine histiocyticmalignancies with canine lymphoma. Chromosomes were segmented toidentify subchromosomal regions that were highly significantly differentin terms of frequency of an aberration in group A vs. group B, and hadto meet a minimum p-value of 1×10⁻¹⁰, based on a two-tailed Fisher'sExact test, as well as a minimum of 55% difference in frequenciesbetween the two groups. The five FASSTT2 segmented regions with thegreatest significant differences between the two cancer types are shownin Table 1.

TABLE 1 Top five FASST2 segmented regions of the canine genome that showsignificant differences in copy number aberration in canine lymphoma(LSA) and histiocytic malignancies (HM). Each region represented a highfrequency copy number loss (deletion), in HM cases that was minimallypresent or absent in LSA cases. Each region is defined by the start andstop base pair position in the canine genome assembly CanFam2. Segments1, 3 and 4 (bold text) are each >200 Kb and so of a size suited todetection and quantification by gold standard fluorescence in situhybridization (FISH) analysis. Regions 2 and 5 are also discriminatoryand would be amenable to use in oligonucleotide based FISH that requiresmaller probe sizes. All five regions would be amenable to detection andquantification using PCR methods to detect and quantify their mean copynumber in cell population. Region Freq. of Freq. of Region Length lossin HM loss in LSA Segment (chromosome: bp) (bp) (%) (%) Differencep-value q-bound 1 chr16: 754805 93.2 7.9 85.3 2.02E−24 5.28E−2131,674,246-32,429,051 2 chr31: 89029 75.0 0.0 75.0 1.63E−23 1.79E−2030,613,619-30,702,648 3 chr31: 362974 72.7 0.0 72.7 1.54E−22 5.92E−2033,346,317-33,709,291 4 chr2: 569151 59.1 0.0 59.1 2.88E−17 9.36E−1631,017,808-31,586,959 5 chr30: 18965 68.2 0.0 68.2 1.11E−20 1.10E−1842,742,706-42,761,671

Statistical Analysis.

Using the frequencies provided for the deletions in HM and LSA tissues,the measures of association and potential predictive performance werecalculated for the three largest of the top five regions (i.e. segments1, 3 and 4). These three regions were selected from the top five shownin Table 1 on the basis of their size being >200 kb in length, whichallows copy number to be detected and enumerated using single locusprobe fluorescence in situ hybridization (FISH) analysis using genomicclones such as bacteria artificial chromosomes (BACs).

Several statistical measures were calculated.

-   -   First, the relative risk was calculated. As calculated, the risk        ratio can be interpreted as the overall risk of a dog being a HM        given that it has a copy number loss, compared to the overall        risk that a dog is a LSA given that it has a copy number loss.        Relative risk (RR) is simply the probability or relationship        between two events. For example, a relative risk of 10 would        indicate that a dog with the aberration would be ten times more        likely to be a HM than a LSA.    -   Second, the odds ratio was calculated. As calculated, the odds        ratio can be interpreted as the odds of a dog being a HM given        that it has a copy number loss compared to the odds that a dog        is a LSA given that it has a copy number loss. Instead of using        pure percentages (like in RR), OR uses the ratio of odds. The OR        explains the ‘odds’ not in its colloquial definition (i.e.        chance) but rather on its statistical definition, which is the        probability of an event over (divided by) the probability of a        certain event not happening.    -   Third, the sensitivity and specificity were calculated.        Sensitivity measures the proportion of actual positives that are        correctly identified as such (in this case the percentage of HM        dogs who are correctly identified as being HM). Specificity        measures the proportion of negatives, which are correctly        identified (in this case the percentage of LSA dogs who are        correctly identified as being LSA).    -   Fourth, an overall misclassification rate was calculated. This        measure tells the percentage of dogs that are misclassified by        this marker. The accuracy of the test overall would simply be        one minus (1−) the misclassification rate.

Additionally, 95% confidence intervals were calculated for each of thesemeasures for each region.

The statistical findings and their interpretations are presented foreach of the three regions individually in tables 2, 3 and 4

TABLE 2 Statistical information regarding copy number decrease ofSegment 1: chr16: 31,674,246-32,429,051 when comparing cells from HM tothose from LSA 95% Confidence Measure Value Interval Relative Risk26.776 9.717 100.613 Odds Ratio 158.875 35.494 836.730 Sensitivity 0.9320.832 0.981 Specificity 0.921 0.877 0.942 Misclassification 0.076 0.0460.136 Rate

TABLE 3 Statistical information regarding copy number decrease ofSegment 3: chr31: 33,346,317-33,709,291 when comparing cells from HM tothose from LSA 95% Confidence Measure Value Interval Relative Risk 9.4176.383 9.417 Odds Ratio Infinite 47.901 Infinite Sensitivity 0.727 0.6440.727 Specificity 1.00 0.964 1.00 Misclassification 0.083 0.083 0.133Rate

TABLE 4 Statistical information regarding copy number decrease ofSegment 4: chr2: 31,017,808-31,586,959 when comparing cells from HM tothose from LSA 95% Confidence Measure Value Interval Relative Risk 6.6114.694 6.611 Odds Ratio Infinite 26.795 Infinite Sensitivity 0.591 0.5060.591 Specificity 1.00 0.963 1.00 Misclassification 0.124 0.124 0.175Rate

Combinatorial Analysis.

To evaluate the potential predictive power of a multivariate model(using up to all three regions together, with gain and loss informationfor all three regions included), a decision tree model was constructedusing the J48 algorithm (Ross Quinlan (1993). C4.5: Programs for MachineLearning. Morgan Kaufmann Publishers, San Mateo, Calif.) and theresulting tree shown below.

CFA16=0.0: LSA (93.0/2.0)

CFA16=−

|CFA31=−: HS/MH (27.0)

|CFA31=0.0

∥CFA2=0.0: LSA (5.0/1.0)

∥CFA2=−: HS/MH (6.0)

∥CFA2=+: HS/MH (0.0)

∥CFA2=CFA2: HS/MH (0.0)

|CFA31=+

∥CFA2=0.0: LSA (5.0/1.0)

∥CFA2=−: HS/MH (3.0)

∥CFA2=+: HS/MH (0.0)

∥CFA2=CFA2: HS/MH (0.0)

|CFA31=CFA31: HS/MH (0.0)

CFA16=CFA16: LSA (0.0)

CFA16=+: LSA (2.0)

As predicted, combining two or more of the segments, in decreasing orderof individual significance, serves to increase the power of this modelto separate these two cancer types, as shown in the table 5

TABLE 5 Summary of statistical significance of an assay when using acombinatorial approach of the three key genomic segments 1, 3 and 4.Segment(s) evaluated Segment Segments Segments 1 only 1 + 3 1 + 3 + 4Sensitivity 0.932 0.929 0.973 Specificity 0.921 0.936 0.972 Area UnderCurve — 0.936 0.971 Misclassification Rate 0.076 0.071 0.028

Detection and quantification of the discriminating segments were furtherevaluated to assess if the copy number of these segments was able tofurther distinguish between histiocytic malignancies andhemangiosarcoma. To accomplish this, DNA was isolated from 84 cases ofhemangiosarcoma [histopathologically confirmed] and each was assessedfor copy number of segment 3 by droplet digital PCR. Comparison to thedata from histiocytic malignancies resulted in a Receiver Operator Curveof 0.865 (86.5%), with an associated specificity and sensitivity of88.1% and 77.8% respectively for a positive diagnosis of a histiocyticmalignancy.

ASPECTS OF THE DISCLOSURE

The invention is based on the evaluation of neoplastic cells obtainedfrom canine tumor specimens to determine the copy number status ofregions of the canine genome identified as segments 1, 3 and 4 above.Combining the copy number data for all three segments provides 97.3%sensitivity and 97.2% specificity to distinguish between a caninehistiocytic neoplasm and a canine lymphoma. Assessment of copy numberstatus of region 3 alone in histiocytic malignancies and hemangiosarcomaprovides sensitivity and specificity of 88.1% and 77.8%, respectivelyfor a positive diagnosis of a histiocytic malignancy, while assessmentof the copy number status of region 3 alone in all three diseasesprovides and area under the Receiver Operator Curve of 0.894 (89.4%), a94% specificity and 77.8% sensitivity for a positive diagnosis of ahistiocytic malignancy. Detection and quantification of the copy numberstatus of one or more of these segments may be performed by a variety oflaboratory based approaches including, but not limited to, fluorescencein situ hybridization (FISH), comparative genomic hybridization,quantitative PCR, digital PCR and next generation sequencing read depth.

The gold standard assay for detecting and quantifying DNA copy numberchanges in cells currently is by fluorescence in situ hybridization(FISH) analysis. To demonstrate the practical means by which theinvention may be used to assess individual patients, we have used FISHanalysis with single locus probes (individually or forming a contig)designed to detect and quantify the three informative segments of thecanine genome located described above, representing regions of CFA 16,31 and 2.

The following examples serve to illustrate the present invention and arenot intended to limit the scope of the claimed invention in any way.

FISH analysis may be performed using any single locus probe, or probepools, that will allow detection and quantification of each region beingevaluated. Such probes may comprise, but are not limited to, one or moreclones of genomic DNA segments within the target region, or pools ofoligonucleotides within the target regions. Regardless of probecomposition, each may be labeled with a hapten (e.g., bio-x-dNTP ordig-x-dNTP) or a fluorochrome (eg Alexa-fluor-dNTP,Spectrum-fluor-dNTP), hybridized to the cells of interest using routinein situ hybridization protocols, and hybridization sites detected andenumerated using routine fluorescence microscopy with appropriatefluorescence filters and image acquisition tools and software.Assessment of individual cells provided a cell to cell comparison withinthe cell population being assessed and analysis of multiple cells in apatient specimen allow derivation of the mean DNA copy number of thesegments in the cell population.

In this example, for the purposes of FISH analysis in cells derived fromeither fresh tumor tissue or fixed tumor tissue, overlapping canine BACprobes were selected for each of the three segments from the CHORI-82BAC library https://bacpac.chori.org/library.php?id=253) as show inTable 6.

TABLE 6 Canine BAC clones from the CHORI-82 library(https://bacpac.chori.org/library.php?id=253) used to generate probes todetect and quantify three regions of the canine genome using FISHanalysis of cells derived from fresh or fixed tissue specimens. Thepositions (in base pairs) were obtained from the CanFam2 genome assemblyin the UCSC Genome browser gateway athttp://genome.csdb.cn/cgi-bin/hgGateway?db=canFam2. CHORI82 Start StopTotal size of Segment clone position position probed region 1 277C0531683415 31891592 chr16: 31,674,246-32,429,051 287P11 32018044 32194654087C13 32168481 32383135 699720 3 285I09 33394572 33589394 chr31:33,346,317-33,709,291 300P10 33425560 33587018 308N22 33475117 33674529279957 4 506M16 31246128 31454594 chr2: 31,017,808-31,586,959 509P0731302995 31478958 O13D24 31330135 31519839 273711

FISH of these probes to non-neoplastic (control) cells is shown in FIG.1, FISH of the probes to cells from a case of a histiocytic neoplasm areshown in FIG. 2 and FISH of the probes to cells from a case of caninelymphoma are shown in FIG. 3.

An additional example of use of this approach is with droplet digitalPCR (ddPCR), also used to detect and quantify aberrant DNA copy number.In this example a custom ddPCR assay was used to quantify region 3 (CFA31). These data demonstrated that this approach separated histiocyticmalignancies from lymphoma and hemangiosarcoma with high specificity andsensitivity (0.940 and 0.778, respectively) (FIGS. 4 and 5).

SUMMARY

These data indicate a significant difference in the DNA copy numberstatus of three regions of the canine genome defined above whenevaluated in tumor samples derived from confirmed cases of caninelymphoma, hemangiosarcoma, and histiocytic malignancies. The dataprovided indicate that a resulting assay for copy number status, even ifjust based on assessment of segment 1 (CFA 16) alone, would offer veryhigh specificity (0.921) and sensitivity (0.931) to separate a diagnosisof lymphoma from that of a histiocytic malignancy. Addition of segments2 (CFA 31) and 4 (CFA 2) increases overall specificity and sensitivityto 0.972 and 0.973, respectively in the comparison of lymphoma tohistiocytic malignancy. Further, the evaluation of segment 3 (CFA 31)alone, offers very high specificity (0.940) and high sensitivity (0.778)to discriminate between canine histiocytic malignancies and lymphoma andhemangiosarcoma. These numbers are higher than many assays currentlyavailable in the human testing space and indicate that any means todetect and quantify these three segments in canine cells would allow ahigh level of confidence in determining if the cells evaluated are froman histiocytic neoplasm or lymphoma, or hemangiosarcoma. An example ofreduction to practice of such an assay was presented, using three BACcontigs as differentially labeled FISH probes, to detect and quantifycopy number of all three segments in tumor cells. In addition a furtherexample was presented using droplet digital PCR to detect and quantitycopy number of region 3.

7. REFERENCES

-   1. Andrea Y. Angstadt, Venugopal Thayanithy, Subbaya Subramanian,    Jaime F. Modiano, and Matthew Breen (2012). A genome-wide approach    to comparative oncology: High-resolution oligonucleotide aCGH of    canine and human OS pinpoints shared microaberrations. Cancer    Genetics. 205(11):572-587-   2. Benoit Hedan, Rachael Thomas, Alison Motsinger-Reif, Jérôme    Abadie, Catherine André, John Cullen and Matthew Breen (2011).    Molecular cytogenetic characterization of canine histiocytic    sarcoma: A spontaneous model for human histiocytic cancer identifies    deletion of tumor suppressor genes and highlights influence of    genetic background on tumor behavior. BMC Cancer 2011, 11:201 doi:    10.1186/1471-2407-11-201 (published May 26, 2011)-   3. Thomas, R., E. L. Seiser, A. A. Motsinger-Reif, L. Borst, V. E.    Valli, K. Kelley, S. E. Suter, D. Argyle, K. Burgess, J. Bell, K.    Lindblad-Toh, J. F. Modiano and M. Breen (2011). “Refining    tumor-associated aneuploidy through ‘genomic recoding’ of recurrent    DNA copy number aberrations in 150 canine non-Hodgkin's lymphomas.”    Leukemia and Lymphoma 52(7):1321-1335.

It is to be understood that, while the invention has been described inconjunction with the detailed description, thereof, the foregoingdescription is intended to illustrate and not limit the scope of theinvention. Other aspects, advantages, and modifications of the inventionare within the scope of the claims set forth below. All publications,patents, and patent applications cited in this specification are hereinincorporated by reference as if each individual publication or patentapplication were specifically and individually indicated to beincorporated by reference.

What is claimed is:
 1. A method for treating a dog with lymphoma, themethod comprising: (a) measuring copy numbers of CFA 2, CFA 16, and CFA31 in a biological sample from a dog suspected of having lymphoma or ahistiocytic malignancy, wherein: (i) the biological sample comprisesneoplastic cells; and (ii) the copy numbers of CFA 2, CFA 16, and CFA 31are measured by aberrations at CFA chr2:31,017,808-31,586,959, CFAchr16:31,674,246-32,429,051, and CFA chr31:33,346,317-33,709,291 fromCamFam2, respectively; (b) detecting a normal or elevated copy number atCFA 2, CFA 16, and CFA 31 compared to a normal control in the biologicalsample; (c) diagnosing the dog with lymphoma; and (d) treating the dogwith standard of care (SOC) chemotherapy using either single agent ormultiagent protocols.
 2. The method of claim 1, wherein the copy numbersare measured by fluorescence in situ hybridization (FISH).
 3. The methodof claim 1, wherein the copy numbers are measured by polymerase chainreaction (PCR).
 4. The method of claim 1, wherein the copy numbers aremeasured by comparative genomic hybridization (CGH).
 5. The method ofclaim 1, wherein the copy numbers are measured by next generationsequencing.
 6. The method of claim 1, wherein the biological sample is atissue sample.
 7. The method of claim 1, wherein the sample is afresh-frozen sample.
 8. The method of claim 1, wherein the sample is afresh sample.
 9. The method of claim 1, wherein the sample is aformalin-fixed, paraffin-embedded sample.
 10. The method of claim 1,wherein the copy numbers at CFA 2, CFA 16, and CFA 31 are measured withprobes of about 15 to about 1×10⁶ nucleotides in length.
 11. The methodof claim 10, wherein the copy numbers are measured with probes of about5,000 to about 800,000 nucleotides in length.
 12. The method of claim10, wherein the copy numbers are measured with probes of about 100,000to about 400,000 nucleotides in length.
 13. A method for selecting andtreating a dog suspected of having a canine lymphoma, the methodcomprising: (a) providing a dog suspected of having a lymphoma or ahistiocytic malignancy; (b) measuring copy numbers of CFA 2, CFA 16, andCFA 31 in a biological sample from the dog, wherein: (i) the biologicalsample comprises cells obtained directly from a suspected neoplasticmass; and (ii) the copy numbers of CFA 2, CFA 16, and CFA 31 aremeasured by aberrations at CFA chr2:31,017,808-31,586,959, CFAchr16:31,674,246-32,429,051, and CFA chr31:33,346,317-33,709,291 fromCamFam2, respectively; (b) detecting normal or elevated copy number atCFA 2, CFA 16, and CFA 31 compared to a normal control in the biologicalsample; (c) diagnosing the dog with lymphoma; and (d) treating the dogwith standard of care (SOC) chemotherapy using either single agent ormultiagent protocols.
 14. The method of claim 13, wherein the copynumbers at CFA 2, CFA 16, and CFA 31 are measured with probes of about15 to about 1×10⁶ nucleotides in length.
 15. The method of claim 14,wherein the copy numbers are measured with probes of about 5,000 toabout 800,000 nucleotides in length.
 16. The method of claim 14, whereinthe copy numbers are measured with probes of about 100,000 to about400,000 nucleotides in length.